/*
 * Encog(tm) Core v3.4 - Java Version
 * http://www.heatonresearch.com/encog/
 * https://github.com/encog/encog-java-core
 
 * Copyright 2008-2017 Heaton Research, Inc.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *   
 * For more information on Heaton Research copyrights, licenses 
 * and trademarks visit:
 * http://www.heatonresearch.com/copyright
 */
package org.encog.neural.networks.training.propagation;

public interface GradientWorkerOwner {
	/**
	 * Called by the worker threads to report the progress at each step.
	 * 
	 * @param gradients
	 *            The gradients from that worker.
	 * @param error
	 *            The error for that worker.
	 * @param ex
	 *            The exception.
	 */
	public void report(final double[] gradients, final double error,
			final Throwable ex);
	
	/**
	 * @return How much to apply l1 regularization penalty, 0 (default) for none.
	 */
	public double getL1();

	/**
	 * @return How much to apply l2 regularization penalty, 0 (default) for none.
	 */
	public double getL2();

}
